An Extension of MOEA/D to Constrained Optimization and Adaptive Weight Adjustment
Yusuke Yasuda, Wataru Kumagai, Kenichi Tamura, Keiichiro Yasuda · IEEJ Transactions on Electronics Information and Systems · 2021
An extended Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D) with adaptive weight adjustment is proposed in this letter. The proposed method facilitates the search on the constraint boundary by adaptively adjusting the weights in the search process. The search performance of the proposed method is shown to be superior to that of the conventional method through numerical experiments using a constrained convex optimization problem.